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Authors: Ana Costa 1 ; Daniel Rodrigues 2 ; Marina Castro 2 ; Sofia Assis 2 and Hélder P. Oliveira 3 ; 4

Affiliations: 1 Faculty of Engineering of the University of Porto, Portugal ; 2 Adapttech, Porto, Portugal ; 3 Faculty of Sciences of the University of Porto, Portugal ; 4 INESC-TEC, Porto, Portugal

Keyword(s): Principal Component Analysis, Point Cloud Registration, Statistical Shape Models, Lower Limb Sockets, 3D Scanning.

Abstract: Lower limb amputation is a condition affecting millions of people worldwide. Patients are often prescribed with lower limb prostheses to aid their mobility, but these prostheses require frequent adjustments through an iterative and manual process, which heavily depends on patient feedback and on the prosthetist’s experience. New computer-aided design and manufacturing technologies have been emerging as a way to improve the fitting process by creating virtual socket models. Statistical Shape modelling was used to create 3D models of transtibial (TT) and transfemoral (TF) sockets. Their generalization errors were, respectively, 6.8 ± 1.8 mm and 10.5 ± 1.6 mm, while specificity errors were 9.7 ± 0.6 mm and 9.8 ± 0.2 mm. In both models, a visual analysis showed that biomechanically meaningful features were captured: the largest variations found for both types were in the length of the residual limb and in the perimeter variation along the limb. The results obtained proved that statistica l shape modelling methods can be applied to TF and TT sockets, with several potential applications in the orthoprosthetic field: generation of new plausible shapes and on-demand socket design adjustments. (More)

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Paper citation in several formats:
Costa, A.; Rodrigues, D.; Castro, M.; Assis, S. and Oliveira, H. (2021). Embedding Anatomical Characteristics in 3D Models of Lower-limb Sockets through Statistical Shape Modelling. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP; ISBN 978-989-758-488-6; ISSN 2184-4321, SciTePress, pages 528-535. DOI: 10.5220/0010339805280535

@conference{visapp21,
author={Ana Costa. and Daniel Rodrigues. and Marina Castro. and Sofia Assis. and Hélder P. Oliveira.},
title={Embedding Anatomical Characteristics in 3D Models of Lower-limb Sockets through Statistical Shape Modelling},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP},
year={2021},
pages={528-535},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010339805280535},
isbn={978-989-758-488-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP
TI - Embedding Anatomical Characteristics in 3D Models of Lower-limb Sockets through Statistical Shape Modelling
SN - 978-989-758-488-6
IS - 2184-4321
AU - Costa, A.
AU - Rodrigues, D.
AU - Castro, M.
AU - Assis, S.
AU - Oliveira, H.
PY - 2021
SP - 528
EP - 535
DO - 10.5220/0010339805280535
PB - SciTePress